Airborne infectious disease is often controlled using filtration-based personal protective equipment (PPE), such as masks. However, such disease prevention measures have seen mixed use by the public, can be uncomfortable to wear over long periods of time, and produce significant levels of solid waste.

An alternative to traditional masking is to enclose a UV source within a personal-scale reactor that a user breathes through and disinfects the air directly. In this work, a set of prototype personal-scale reactors were developed that utilize UV-C LEDs. Experimental measurements of the UV-C fluence rate within the reactors were conducted using a microfluorescent silica detector. Biological experiments were also conducted, where an aerosolized challenge agent was passed through the reactor, and the fraction of agent inactivation by UV-C exposure was quantified as a function of airflow rate.

Experimental results were compared to simulations, in which computational fluid dynamics and optical simulations were used to simulate the inactivation of an infective agent resulting from UV exposure. The disinfection simulation results were similar to the experimental data, showing how computational modeling can be used to inform UV-C-based PPE designs that could be later experimentally investigated. Both simulations and experiments indicated that it is possible to achieve in excess of 1.3 log10 disinfection using personal-scale reactors, making them more effective than an N95 mask, even when disinfecting airflow rates that correspond to human respiration rates during moderate exercise. This is especially true when lining the walls of the reactors with reflective material that allows photon recycling within the reactor. This work presents a proof-of-concept for future UV-based PPE design that can become a standard tool for disease control and prevention.